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Paulo Blikstein. (under review) Computational alchemy via representational
magic: epistemic affordances of re-presenting complex scientific phenomena.
Journal of the Learning Sciences.
Paulo Blikstein. (in print). New technologies for learning and the future
of public education in Brazil. Nakahodo, S. and Moura, M. (Eds.) Globalized Brazilians.
In this paper, we describe techniques to use multimodal learning analytics to analyze data collected around an interactive tangible learning environment. In a previous study , we designed and evaluated a Tangible User Interface (TUI) where dyads of students were asked to learn about the human hearing system by reconstructing it. In the current study, we present the analysis of the data collected in form of logs, both from students’ interaction with the tangible interface and as well as from their gestures, and we describe how we extracted meaningful predictors for students’ learning from those two datasets. First we show how Natural Language Processing (NLP) techniques can be used on the tangible interface logs to predict learning. Secondly, we explored how KinectTM data can inform “in-situ” interactions around a tabletop (i.e. using clustering algorithms to find prototypical body positions). Finally, we fed those features to a machine-learning classifier (Support Vector Machine) and split students in two groups after performing a median split on their learning scores. We found that we were able to predict students’ learning gains (i.e. being above or belong the median split) with very high accuracy. We discuss the implications of those results for analyzing data from rich, multimodal learning environments.Citation:
Schneider, B., & Blikstein, P. (accepted). Unraveling Students’ Interaction
Around a Tangible Interface using Multimodal Learning Analytics. In Proceedings of the 7th International Conference on Educational Data Mining, London, UK (Vol. ?, No. ?, p. ??).
Worsley, M. and Blikstein, P. (accepted). Leveraging Multimodal Learning
Analytics to Differentiate Student Learning Strategies.
In this paper we demonstrate an approach to supporting students’ engagement in combined physical experimentation and virtual modeling. We present a study that utilizes a scientific inquiry framework which links students’ physical experimentation with their use of computer modeling in real time, which we call “Bifocal Modeling.” In the case of the Bifocal Modeling activities discussed here, a group of high-school students designed computer models of bacterial growth through reference to a physical experiment they were conducting, and they were able to validate the effectiveness of their model against the results from their experiment. Our findings suggests that as students compare their virtual models with physical experiments, they encounter “discrepant events” that contradict their existing conceptions and elicit a disequilibrium. This experience of conflict encourages students to further examine their ideas and hypothesis, seek more accurate explanations of the observed natural phenomena, improving the design of their computer models.Citation:
Furhmann, T., Salehi, S. & Blikstein, P. (2014). A Tale of Two Worlds:
Using Bifocal Modeling to Find and Resolve “Discrepant Events” Between
Physical Experiments and Virtual Models in Biology. Proceedings of the
International Conference of the Learning Sciences (ICLS 2014), Madison, WI.
Worsley, M. and Blikstein, P. (2014). An Approach for Combining Qualitative
Analysis with Learning Analytics to Study Learning Processes in Open-Ended
Environments. Paper Presented at the 2014 American Education Research
Association (AERA) Annual Conference.
Learning analytics and educational data mining are introducing a number of new techniques and frameworks for studying learning. The scalability and complexity of these novel techniques has afforded new ways for enacting education research and has helped scholars gain new insights into human cognition and learning. Nonetheless, there remain some domains for which pure computational analysis is currently infeasible. One such area, which is particularly important today, is open‐ended, hands‐on, engineering design tasks. These open‐ended tasks are becoming increasingly prevalent in both K–12 and post‐secondary learning institutions, as educators are adopting this approach in order to teach students real‐world science and engineering skills (e.g., the “Maker Movement”). This paper highlights findings from a combined human–computer analysis of students as they complete a short engineering design task. The study uncovers novel insights and serves to advance the field’s understanding of engineering design patterns. More specifically, this paper uses machine learning on hand‐coded video data to identify general patterns in engineering design and develop a fine‐grained representation of how experience relates to engineering practices. Finally, the paper concludes with ideas on how the specific findings from this study can be used to improve engineering education and the nascent field of “making” and digital fabrication in education. We also discuss how human–computer collaborative analyses can grow the learning analytics community and make learning analytics more central to education research.Citation:
Worsley, M. and Blikstein, P. (2014). Analyzing Engineering Design through
the Lens of Computation. Journal of Learning Analytics.
Multimodal analysis has had demonstrated effectiveness in studying and modeling several human-human and human-computer interactions. In this paper, we explore the role of multimodal analysis in the service of studying complex learning environments. We use a semi-automated multimodal method to examine how students learn in a hands-on, engineering design context. Specifically, we combine, audio, gesture and electro-dermal activation data from a study (N=20) in which students were divided into two experimental conditions. The two experimental conditions, example-based reasoning and principle-based reasoning, have previously been shown to be associated with different learning gains and different levels of design quality. In this paper we study how the two experimental conditions differed in terms of their practices and processes. The practices included four common multimodal behaviors, that we’ve entitled ACTION, TALK, STRESS and FLOW. Furthermore, we show that individuals from the two experimental conditions differed in their usage of the four common behavior both on aggregate, and when we model their sequence of actions. Details concerning the data, analytic technique, interpretation and implications of this research are discussed.Citation:
Worsley, M. and Blikstein, P. (2014). Deciphering the Practices and Affordances of Different Reasoning Strategies through Multimodal Learning Analytics. In Proceedings of the 2014 ACM workshop on Multimodal Learning Analytics Workshop and Grand Challenge (MLA ’14). ACM, New York, NY, USA, 21-27.
Constructionism can be a powerful framework for teaching complex content to novices. At the core of constructionism is the suggestion that by enabling learners to build creative artifacts that require complex content to function, those learners will have opportunities to learn this content in contextualized, personally meaningful ways. In this paper, we investigate the relevance of a set of approaches broadly called “educational data mining” or “learning analytics” (henceforth, EDM) to help provide a basis for quantitative research on constructionist learning which does not abandon the richness seen as essential by many researchers in that paradigm. We suggest that EDM may have the potential to support research that is meaningful and useful both to researchers working actively in the constructionist tradition but also to wider communities. Finally, we explore potential collaborations between researchers in the EDM and constructionist traditions; such collaborations have the potential to enhance the ability of constructionist researchers to make rich inferences about learning and learners, while providing EDM researchers with many interesting new research questions and challenges.Citation:
Berland, M., Baker, R.S. & Blikstein, P. (2014). Educational Data Mining
and Learning Analytics: Applications to Constructionist Research.
Technology, Knowledge and Learning, Volume 19, Issue 1-2, pp 205-220.
Constructionism and the Maker Movement are becoming increasingly prevalent and increasingly popular. Makerspaces and Fablabs are being developed in schools, libraries, museums and community centers around the world. However, as this movement grows it is important to continue researching, refining and improving the best practices within these innovative environments. In this paper we present a pair of studies that document 1) common strategies that students use in hands-on learning, and 2) how those strategies impact student performance and learning. Specifically, we show that students who engage in a short principle-based reasoning intervention, outperform their peers who use example-based reasoning both in terms of the quality of their designs, and in terms of knowledge construction. Based on the results of these studies we propose that short, appropriately targeted, generative activities be more broadly used in constructionist learning environments. The generative activities will help promote “object closeness” and improve the current state of making in education.Citation:
Worsley, M. and Blikstein, P. (2014). Making Smarter not Harder: Using
Principle-based Reasoning to Promote Object Closeness and Improve Making.
In Proceedings of the 2014 FabLearn Conference.
This paper summarizes the third Multimodal Learning Analytics Workshop and Grand Challenges (MLA’14). This subfield of Learning Analytics focuses on the interpretation of the multimodal interactions that occurs in learning environments, both digital and physical. This is a hybrid event that includes presentations about methods and techniques to analyze and merge the different signals captured from these environments (workshop session) and more concrete results from the application of Multimodal Learning Analytics techniques to predict the performance of students while solving math problems or presenting in the classroom (challenges sessions). A total of eight articles will be presented in this event. The main conclusion from this event is that Multimodal Learning Analytics is a desirable research endeavour that could produce results that can be currently applied to improve the learning process.Citation:
Ochoa, X., Worsley, M., Chiluiza, K., and Luz, S. (2014). MLA’14: Third Multimodal Learning Analytics Workshop and Grand Challenges. In Proceedings of the 16th International Conference on Multimodal Interaction (ICMI ’14). ACM, New York, NY, USA, 531-532.
The recent emergence of several low-cost, high resolution, multimodal sensors has greatly facilitated the ability for researchers to capture a wealth of data across a variety of contexts. Over the past few years, this multimodal technology has begun to receive greater attention within the learning community. Specifically, the Multimodal Learning Analytics community has been capitalizing on new sensor technology, as well as the expansion of tools for supporting computational analysis, in order to better understand and improve student learning in complex learning environments. However, even as the data collection and analysis tools have greatly eased the process, there remain a number of considerations and challenges in framing research in such a way that it lends to the development of learning theory. Moreover, there are a multitude of approaches that can be used for integrating multimodal data, and each approach has different assumptions and implications. In this paper, I describe three different types of multimodal analyses, and discuss how decisions about data integration and fusion have a significant impact on how the research relates to learning theories.Citation:
Worsley, M. (2014). Multimodal Learning Analytics as a Tool for Bridging
Learning Theory and Complex Learning Behaviors. In Proceedings of the 2014
ACM workshop on Multimodal Learning Analytics Workshop and Grand Challenge
(MLA ’14). ACM, New York, NY, USA, 1-4.
New high-frequency, automated data collection and analysis algorithms could offer new insights into complex learning processes, especially for tasks in which students have opportunities to generate unique open-ended artifacts such as computer programs. These approaches should be particularly useful because the need for scalable project-based and student-centered learning is growing considerably. In this article, we present studies focused on how students learn computer programming, based on data drawn from 154,000 code snapshots of computer programs under development by approximately 370 students enrolled in an introductory undergraduate programming course. We use methods from machine learning to discover patterns in the data and try to predict final exam grades. We begin with a set of exploratory experiments that use fully automated techniques to investigate how much students change their programming behavior throughout all assignments in the course. The results show that students’ change in programming patterns is only weakly predictive of course performance. We subsequently hone in on 1 single assignment, trying to map students’ learning process and trajectories and automatically identify productive and unproductive (sink) states within these trajectories. Results show that our process-based metric has better predictive power for final exams than the midterm grades. We conclude with recommendations about the use of such methods for assessment, real-time feedback, and course improvement.Citation:
Blikstein, P., Worsley, M., Piech, C., Gibbons, A., Sahami, M., & Cooper,
S. (2014). Programming Pluralism: Using Learning Analytics to Detect
Patterns in Novices’ Learning of Computer Programming. International
Journal of the Learning Sciences. Vol. 23, Iss. 4. 561-599.
Prior research suggests that experts and novices employ markedly different approaches to engineering design tasks. For example, novice designers commonly use trial and error, which researchers liken to backward-reasoning. Experts use forward-reasoning, which allows them to accurately predict the impact of certain decisions. In this paper, we present a complementary conceptualization for how experience affects design approaches. We liken backward-reasoning to example-based reasoning, and forward-reasoning to principle-based reasoning. In study 1 (N=13) students complete an engineering design activity. A qualitative analysis shows clear instances of example- and principle-based reasoning strategies. Study 2 (N=20) compares the efficacy of the two approaches by using a between-subject design. We find that principle-based reasoning improves the quality of designs (p < 0.01) and learning of important engineering principles (p < 0.001). This suggests that hands-on learning environments may benefit from encouraging students to employ principle-based reasoning.Citation:
Worsley, M. and Blikstein, P. (2014). The Impact of Principle-Based
Reasoning on Hands-on, Project-Based Learning. In Proceedings of the 2014
International Conference of the Learning Sciences.
In this paper, we propose multimodal learning analytics as a new approach for studying the intricacies of different learning mechanisms. More specifically, we conduct two analyses of a hands-on, engineering design study (N=20) in which students received different treatments. In the first analysis, we used machine learning to analyze hand-labeled video data. The findings of this analysis suggest that one of the treatments resulted in students initially engaging in more planning, while the other resulted in students initially engaging in more building. In accordance with prior literature, beginning with dedicated planning tends to be associated with improved success and improved learning. In the second analysis we introduce a completely automated multimodal analysis of speech, actions and stress. This automated analysis uses multimodal states to show that students in the two conditions engaged in different amounts of speech and building during the second half of the activity. These findings mirror prior work on teamwork, expertise and engineering education. They also represent two novel approaches for studying complex, non-computer mediated learning environments and provide new ways to understand learning.Citation:
Worsley, M. and Blikstein, P. (2014). Using Multimodal Learning Analytics
to Study Learning Mechanisms. In Proceedings of the 2014 Educational Data
In this paper, we describe results from a pilot study designed to understand the differences in eye tracking patterns between students with low and high performance in three engineering-related computer games that require spatial ability and visual imagery. In the first game, gears and chains had to be connected until all gears spun. In the second game, students had to ensure that no two lines were intersecting. In the last game, students placed gears in specific places to put objects on the screen in motion. Scientific literature establishes that these abilities are related with math learning and math performance and understanding differences in visual processing and attention dedicated to spatial stimuli can be helpful in making positive interventions in science education.Citation:
Gomes, J. Yassine, M., Worsley, M., Blikstein, P. (2013) Analysing
Engineering Expertise of High School Students Using Eye Tracking and
Multimodal Learning Analytics. In Proceedings of the Educational Data
Mining 2013 (EDM ’13). Memphis, TN, USA. 375-377.
Frameworks that create synergies across disciplines provide a powerful means for learning by relating concepts from the different fields that are usually difficult to grasp individually. We discuss the design of the BeatTable, a microworld that uses the relation between mathematics and music to engage learners in using ratios and proportions to create rhythms and learn about musical composition. The BeatTable is a physical table with a digital environment that can be controlled by tangible instruments, and through immediate auditory and visual feedback makes salient the relationships between math and music. With a low-floor, high-ceiling design philosophy, BeatTable provides learners the opportunity to build on their conceptions about music and to practice and hone their use of ratios and proportions. We present what our design choices, the technology used, and a description of initial user feedback.Citation:
Bumbacher E., Deutsch A., Otero N., & Blikstein P. (in press) “BeatTable: A
Tangible Approach to Rhythms and Ratios” in IDC.
In this paper, I present three case studies of students that represent different phases of interest development and commitment. Based on this analysis, I conclude with four recommendations for better enabling learning across a diverse set of interest levels.Citation:
Worsley, M. and Blikstein, P. (2013). Designing for Diversely Motivated
Learners. Paper Presented at the Digital Fabrication and Making In
Education Workshop at the 2013 Interactive Design for Children Conference
(IDC 2013), New York, NY, USA.
Every few decades or centuries, a new set of skills and intellectual activities become crucial for work, conviviality, and citizenship – often democratizing tasks and skills previously only accessible to experts. Digital fabrication and ‘making’ could be a new and major chapter in this process of bringing powerful ideas, literacies, and expressive tools to children. Today, the range of accepted disciplinary knowledge has expanded to include not only programming, but also engineering and design. In addition, there are calls everywhere for educational approaches that foster creativity and inventiveness. In this chapter, I will first briefly review the history of engineering education to show the rise and fall then rise again of the making and building as curricular foci. I then discuss the theoretical underpinnings of project-based, student-centered, constructionist learning, showing that much of what digital fabrication labs can enact was already predicted and advocated in the theories and writings of John Dewey, Seymour Papert, and Paulo Freire. The following section approaches the educational benefits of digital fabrication and how it could be a unique tool in the hands of progressive educators. In the final part of the chapter I present not only four prototypical episodes that exemplify the advantages and perils of FabLabs in schools, but also some guidelines for the design of learning environments incorporating these types of technologies. See also the related article, “Travels in Troy with Freire: Technology as an Agent of Emancipation” at https://tltl.stanford.edu/publications/papers-or-book-chapters/travels-troy-freire.Citation:
To appear in: Blikstein, P. (2013). Digital Fabrication and ’Making’ in
Education: The Democratization of Invention. In J. Walter-Herrmann & C.
Büching (Eds.), FabLabs: Of Machines, Makers and Inventors. Bielefeld:
Advances in learning analytics are contributing new empirical findings, theories, methods, and metrics for understanding how students learn. It also contributes to improving pedagogical support for students’ learning through assessment of new digital tools, teaching strategies, and curricula. Multimodal learning analytics (MMLA) is an extension of learning analytics and emphasizes the analysis of natural rich modalities of communication across a variety of learning contexts. This MMLA Grand Challenge combines expertise from the learning sciences and machine learning in order to highlight the rich opportunities that exist at the intersection of these disciplines. As part of the Grand Challenge, researchers were asked to predict: (1) which student in a group was the dominant domain expert, and (2) which problems that the group worked on would be solved correctly or not. Analyses were based on a combination of speech, digital pen and video data. This paper describes the motivation for the grand challenge, the publicly available data resources and results reported by the challenge participants. The results demonstrate that multimodal prediction of the challenge goals: (1) is surprisingly reliable using rich multimodal data sources, (2) can be accomplished using any of the three modalities explored, and (3) need not be based on content analysis.Citation:
Morency, L. Oviatt, S., Scherer, S. Weibel, N. and Worsley, M. (2013). ICMI 2013 Grand Challenge Workshop on Multimodal Learning Analytics. In Proceedings of the 15th ACM international conference on Multimodal interaction (ICMI ’13). ACM, New York, NY, USA.
Predicting student knowledge from text has become an increasingly common for automatic grading and assessment. Much of this work, however, hinges on natural language processing techniques that tend to neglect the relative locations of individual words by using a bag of words model. Instead of using this technique we segment text into a bag of utterances. We then use those utterances to examine the extent to which individuals of different levels of expertise paraphrase one another. Results indicate clear distinctions among paraphrase frequencies of the different levels of expertise. Furthermore, results suggest that experts and novices have many of the same intuitions, but that the expert’s knowledge is more accurately applied.Citation:
Worsley, M. & Blikstein P. (in press). Learning to paraphrase: using
paraphrase detection of spoken utterances to predict learner expertise. Paper to be presented at Annual Meeting of the American Education Research
We present and evaluate the design of LightUp, an augmented, learning platform for electronics. LightUp helps children explore engineering and electronics by foregrounding fundamental concepts and backgrounding the extraneous intricacies of circuit construction. LightUp consists of electronic components (e.g. wire, bulb, motor, microcontroller) mounted on blocks that connect to each other magnetically to form circuits. In addition, LightUp provides an “informational lens” through a mobile app that recognizes the components in a photographed circuit and augments the image with visualizations of otherwise invisible circuit behavior. Our study findings demonstrate the experiential learning made possible by augmenting an intuitive circuit-building platform with information that allows children to learn skills that will help them develop engineering skills and agency.Citation:
Joshua Chan, Tarun Pondicherry, and Paulo Blikstein. 2013. LightUp: an augmented, learning platform for electronics. In Proceedings of the 12th International Conference on Interaction Design and Children (IDC ’13). ACM, New York, NY, USA, 491-494.
In this paper we will examine students’ meta-modeling knowledge in the context of their participation in a Bifocal Modeling activity. Bifocal Modeling is an inquiry-based approach for science learning, which incorporates both physical experimentation and virtual modeling. The current study combines three separate case studies of students participating in different implementation modes of the Bifocal Modeling process. Different implementation methods require different modeling practices, and we will examine the consequences of these practices for students’ meta-modeling knowledge. The concern of our investigation will be the ways that students critically evaluate scientific models and their understanding of the limitations of those models. Data suggest that model construction (as opposed to simple interaction) lead to deeper meta-modeling knowledge.Citation:
Tamar Fuhrmann, Shima Salehi, and Paulo Blikstein. 2013. Meta-modeling
knowledge: Comparing model construction and model interaction in bifocal
modeling. In Proceedings of the 12th International Conference on
Interaction Design and Children (IDC ’13). ACM, New York, NY, USA.
New high-frequency data collection technologies and machine learning analysis techniques could offer new insights into learning, especially in tasks in which students have ample space to generate unique, personalized artifacts, such as a computer program, a robot, or a solution to an engineering challenge. To date most of the work on learning analytics and educational data mining has focused on online courses or cognitive tutors, in which the tasks are more structured and the entirety of interaction happens in front of a computer. In this paper, I argue that multimodal learning analytics could offer new insights into students’ learning trajectories, and present several examples of this work and its educational application.Citation:
Paulo Blikstein. 2013. Multimodal learning analytics. In Proceedings of the Third International Conference on Learning Analytics and Knowledge (LAK ’13), Dan Suthers and Katrien Verbert (Eds.). ACM, New York, NY, USA, 102-106.
This workshop, intended for CS educators from middle school through undergrad, will introduce participants to NetLogo. NetLogo is an easy-to-learn multi-agent language and integrated modeling environment in widespread use in classrooms (and research labs) globally. This hands-on tutorial will highlight computational modeling in the natural and social sciences, tie in core computer science concepts, and discuss how to promote student thinking about decentralized systems. The workshop will draw on the presenters’ own experiences teaching courses on computational science, computational art, theory of computation, and educational outreach events. Participants will learn first-hand how NetLogo can enrich a variety of computing courses. NetLogo runs on Mac/Linux/Windows. Laptop required.Citation:
Forrest Stonedahl, David Weintrop, Paulo Blikstein, and Christine Shannon. 2013. NetLogo: teaching with turtles and crossing curricular boundaries (abstract only). In Proceedings of the 44th ACM technical symposium on Computer science education (SIGCSE ’13). ACM, New York, NY, USA, 763-763.
In this paper we describe the development and evaluation of a microworld-based learning environment for neuroscience. Our system, BrainExplorer, allows students to discover the way neural pathways work by interacting with a tangible user interface. By severing and reconfiguring connections, users can observe how the visual field is impaired and thus actively learn from their exploration. An ecological evaluation of BrainExplorer revealed that 1) students who engaged in the open-ended exploration outperformed students who used traditional textbook materials, and 2) correctly sequencing activities is fundamental for improving student performance. Participants who used the tabletop first and then studied a text significantly outperformed participants who read a text first and then used the tabletop. Additionally, those results were best predicted by the quality of students’ verbalizations while using BrainExplorer. Implications are discussed in terms of preparing students for future learning with Tangible User Interfaces.Citation:
Schneider B., Wallace J., Pea, R. & Blikstein P. (2013). Preparing for
Future Learning with a Tangible User Interface: the Case of Neuroscience. IEEE Transactions on Learning Technologies.
Introductory computer science courses are a valuable resource to students of all disciplines. While we often look at students’ end products to judge their proficiency, little analysis is done on the most integral aspect of learning to programming, the process. We also have a hard time quantifying how students’ programming changes over the course of a semester. In order to address these we show how a process-oriented analysis can identify meaningful trends in how programmers develop proficiency across various assignments.Citation:
Worsley, M., & Blikstein, P. (2013). Programming Pathways: A Technique for
Analyzing Novice Programmers’ Learning Trajectories. In Artificial
Intelligence in Education. Springer Berlin Heidelberg. 844-847.
Recent research in CS education has leveraged machine learning techniques to capture students’ progressions through assignments in programming courses based on their code submissions. With this in mind, we present a methodology for creating a set of descriptors of the students’ progression based on their coding styles as captured by different non-semantic and semantic features of their code submissions. Preliminary findings show that these descriptors extracted from a single assignment can be used to predict whether or not a student got help throughout the entire quarter. Based on these findings, we plan on developing a model of the impact of teacher intervention on a student’s pathway through homework assignments.Citation:
Bumbacher E., Sandes A., Deutsch A., & Blikstein P. (in press) “Student
Coding Styles as Predictors of Help-Seeking Behavior” in AIED Memphis.
In this paper, we describe multimodal learning analytics techniques for understanding and identifying expertise as students engage in a hands-on building activity. Our techniques leverage process-oriented data, and demonstrate how this temporal data can be used to identify elements of expertise among students. The proposed techniques introduce useful insights in how to segment and analyze this type of data, while also uncovering new ideas about how experts engage in building activities. Finally, this work serves to motivate additional research and development in the area of authentic, automated, process-oriented assessments.Citation:
Marcelo Worsley and Paulo Blikstein. 2013. Towards the development of multimodal action based assessment. In Proceedings of the Third International Conference on Learning Analytics and Knowledge (LAK ’13), Dan Suthers and Katrien Verbert (Eds.). ACM, New York, NY, USA, 94-101.
Scherer,S., Worsley,M. and Morency, L. (2012). 1st international workshop on multimodal learning analytics: extended abstract. In Proceedings of the 14th ACM international conference on Multimodal interaction (ICMI ’12). ACM, New York, NY, USA, 609-610.
In this paper we present a framework for examining meaningful changes in students’ identity in relation to science and engineering. These identity changes could represent useful indicators for characterizing student engagement and interest in constructionist, project-based learning environments. The framework is described using data from a study with 12 high-school students that in which learners spent 6-hours a day in a digital fabrication lab for eight weeks.Citation:
Worsley, M. & Blikstein P. (2012). A framework for characterizing student
changes in student identity during constructionist learning activities. Paper presented at Constructionism 2012.
This paper describes two methods for analyzing student gaze in computer-mediated learning applications. More specifically, we demonstrate how to use eye-tracking data from an agent based modeling study to identify meaningful patterns in student learning processes. We do this by using techniques from network analysis and natural language processing which allow us to identify statistically significant differences among our two conditions. Finally, we conclude by motivating a larger study that will further utilize these techniques.Citation:
Worsley, M. & Blikstein P. (2012). An eye for detail: techniques for using
eye tracker data to explore learning in computer-mediated environments. In
the Proceedings of the 2012 International Conference of the Learning Sciences (ICLS 2012).
Blikstein, P., Fuhrmann, T., Greene, D., & Salehi, S. (2012) Bifocal
Modeling Workshop. Proceedings of the International Conference of the Learning Sciences (ICLS 2012), Sydney, Australia.
Computer modeling, and in particular agent-based modeling, has been successfully used in many scientific fields, transforming scientists’ practice. Educational researchers have come to realize its potential for learning, and studies have suggested that students are able to understand concepts above their expected grade level after interacting with curricula that employ modeling and simulation. However, most simulations are ‘on-screen’, without connection to the physical world. Therefore, real-time model validation is challenging with extant modeling platforms. I have designed a technological and pedagogical framework to enable students to connect computer models and sensors in real time, as to validate, compare, and refine their models using real-world data. In this paper, I will focus on both technical and pedagogical aspects, describing pilot studies that suggest a real-to-virtual reciprocity which catalyzes further inquiry toward deeper understanding of scientific phenomena.Citation:
Paulo Blikstein. 2012. Bifocal modeling: a study on the learning outcomes of comparing physical and computational models linked in real time. In Proceedings of the 14th ACM international conference on Multimodal interaction (ICMI ’12). ACM, New York, NY, USA, 257-264.
Blikstein, P., Greene, D., Furhmann, T., & Salehi, S. (2012). Bifocal
Modeling: Combining real and virtual models for science learning in a
school setting. Proceedings of the IDC 2012 Conference, Bremen, Germany.
In this paper, we describe a set of user studies within the Bifocal Modeling (BM) framework. BM juxtaposes physical and computer models using sensor-based and computer modeling technologies, highlighting the discrepancies between ideal and real systems. When creating bifocal models, students build both a physical model with sensors of a given scientific phenomenon, and a computer model of the same phenomenon, connecting the two in real time with a special hardware interface. In this paper, we describe four formats for using BM in the classroom, as well as its affordances and characteristics.Citation:
Paulo Blikstein, Tamar Fuhrmann, Daniel Greene, and Shima Salehi. 2012. Bifocal modeling: mixing real and virtual labs for advanced science learning. In Proceedings of the 11th International Conference on Interaction Design and Children (IDC ’12). ACM, New York, NY, USA, 296-299.
Neuroscience has recently brought many insights into the inner workings of the human brain. The way neuroscience is taught, however, has lagged behind and still relies on direct instruction or textbooks. We argue that the spatial nature of the brain makes it an ideal candidate for hands-on activities coupled with a tangible interface. In this paper we introduce BrainExplorer, a learning environment for teaching neuroscience. BrainExplorer allows users to explore neural pathways on a custom tabletop platform. We conducted an evaluation with 28 participants comparing students who learned neuroscience content through using BrainExplorer with students who learned by reading a textbook chapter. We found that our system promotes learning along 3 dimensions: memorizing scientific terminology, understanding a dynamic system, and transferring knowledge to a new situation.Citation:
Bertrand Schneider, Jenelle Wallace, Roy Pea, and Paulo Blikstein. 2012. BrainExplorer: an innovative tool for teaching neuroscience. In Proceedings of the 2012 ACM international conference on Interactive tabletops and surfaces (ITS ’12). ACM, New York, NY, USA, 407-410.
Blikstein, P. (2012). Building (timely) bridges between learning analytics,
educational data mining and core learning sciences perspectives. In Proceedings of the ICLS (ICLS 2012), Sidney, Australia.
Teaching abstract concepts is notoriously difficult, especially when we lack concrete metaphors that map to those abstractions. Combinatorix offers a novel approach that combines tangible objects with an interactive tabletop to help students explore, solve and understand probability problems. Students rearrange physical tokens to see the effects of various constraints on the problem space; a second screen displays the associated changes in an abstract representation, e.g., a probability tree. Using participatory design, college students in a combinatorics class helped iteratively refine the Combinatorix prototype, which was then tested successfully with five students. Combinatorix serves as an initial proof-of-concept that demonstrates how tangible tabletop interfaces that map tangible objects to abstract concepts can improve problem-solving skills.Citation:
Bertrand Schneider, Paulo Blikstein, and Wendy Mackay. 2012. Combinatorix: a tangible user interface that supports collaborative learning of probabilities. In Proceedings of the 2012 ACM international conference on Interactive tabletops and surfaces (ITS ’12). ACM, New York, NY, USA, 129-132.
In this pilot study we investigated the effect of technological platform on the quality of students’ cognition when analyzing a computer simulation. As an indicator of performance, we measured the percentage of ideal cycles of cognition; an ideal cycle of cognition is defined as having three distinct steps: planning an action, executing it and evaluating its effects. The results of this study suggest that individuals were not affected by the orientation of display; dyads, however, had twice as many ideal cycles of cognition when interacting with a tabletop than with a desktop. We discuss the implications and limitations of those preliminary results for classroom instruction.Citation:
Shima Salehi, Bertrand Schneider, and Paulo Blikstein. 2012. Comparing the effect of interactive tabletops and desktops on students’ cognition. In Proceedings of the 2012 ACM international conference on Interactive tabletops and surfaces (ITS ’12). ACM, New York, NY, USA, 391-394.
Science, Technology, Engineering, and Mathematics (STEM) have received a huge push in education during the past few years. However, current methods to teach STEM concepts often lack the ability to allow students creative and open-ended expression. While some toys on the market try to address these issues, they often fail to fulfill learning affordances to their full potential. Our system, MagneTracks, is a multi-component educational toolkit that permits users to engage in creative, exploratory, and open-ended learning of Newtonian physics. MagneTracks consists of dynamic, tangible, magnetic tracks that attach to a vertical whiteboard, a computer-based tracking program integrated into the Netlogo platform, and curriculum challenge activity cards. MagneTracks is specifically focused on teaching physics concepts but can be used to educate in other STEM fields. Initial user observation has shown positive learning outcomes and high engagement.Citation:
Andrea Miller, Claire Rosenbaum, and Paulo Blikstein. 2012. MagneTracks: a
tangible constructionist toolkit for Newtonian physics. In Proceedings of the Sixth International Conference on Tangible, Embedded and
Embodied Interaction (TEI ’12), Stephen N. Spencer (Ed.). ACM, New York, NY, USA, 253-256.
Despite the potential wealth of educational indicators expressed in a student’s approach to homework assignments, how students arrive at their final solution is largely overlooked in university courses. In this paper we present a methodology which uses machine learning techniques to autonomously create a graphical model of how students in an introductory programming course progress through a homework assignment. We subsequently show that this model is predictive of which students will struggle with material presented later in the class.Citation:
Chris Piech, Mehran Sahami, Daphne Koller, Steve Cooper, and Paulo Blikstein. 2012. Modeling how students learn to program. In Proceedings of the 43rd ACM technical symposium on Computer Science Education (SIGCSE ’12). ACM, New York, NY, USA, 153-160.
Project-based learning has found its way into a range of formal and
informal learning environments. However, systematically assessing these
environments remains a significant challenge. Traditional assessments,
which focus on learning outcomes, seem incongruent with the
process-oriented goals of project-based learning. Multimodal interfaces and
multimodal learning analytics hold significant promise for assessing
learning in open-ended learning environments. With its rich integration of
a multitude of data streams and naturalistic interfaces, this area of
research may help usher in a new wave of education reform by supporting
alternative modes of learning
Worsley, M. (2012). Multimodal Learning Analytics: enabling the future of
learning through multimodal data analysis and interfaces. International Conference on Multimodal Interfaces (ICMI 2012).
In this paper, we present an application framework for enabling the development of gesture and speech based applications for collaborative learning environments. More specifically, we are concerned with combining the affordances of natural interfaces with educational theories concerning embodied cognition to develop an application framework that enables education researchers and practitioners to create enriching multi-modal learning experiences. Furthermore, this paper highlights a user study that explores how students interacted in a multi-user, collaborative space. Our initial findings indicate that these applications are certainly feasible for well-defined learning tasks, but may require machine learning based training in order to be successful in contexts where the vocabulary is more diverse.Citation:
Worsley, M. & Blikstein P. (2012). OpenGesture: a low-cost, easy-to-author
application framework for collaborative, gesture-, and speech-based
learning applications. Paper presented at the Annual Meeting of the American Education Research
Association (AERA 2012).
This paper introduces Process Pad, an interactive, low-cost multi-touch tabletop platform designed to capture students’ thought process and facilitate their explanations. Process Pad is designed to help students improve their thinking skills and meta-cognition in various subjects. The system is intended to dynamically externalize how a student arrives at the final answer. Process Pad enables the documentation of students’ think-aloud narratives that would otherwise be tacit. Our focus is on identifying and understanding key themes in creating opportunities for students to externalize and represent their thought process using multimodal data. From our user observations, we gleaned four design perspectives as essential criteria based upon which we form our design decisions: flexibility, tangibility, collaboration and affordability. Our initial results show that for many users explaining their reasoning or problem-solving procedure is a challenging activity in itself, and for learners to be able to deepen their understanding by narrating or re-enacting a process there would be many intervening steps. To address these challenges we designed scaffolding activities, which made use of the system’s affordances to improve students’ explanation skills.Citation:
Shima Salehi, Jain Kim, Colin Meltzer, and Paulo Blikstein. 2012. Process pad: a low-cost multi-touch platform to facilitate multimodal documentation of complex learning. In Proceedings of the Sixth International Conference on Tangible, Embedded and Embodied Interaction (TEI ’12), Stephen N. Spencer (Ed.). ACM, New York, NY, USA, 257-262.
This paper introduces Process Pad, an interactive, low-cost multi-touch
tabletop platform designed to capture students’ thought process and
facilitate their explanations. Process Pad is designed to help students
improve their thinking skills and meta-cognition in various subjects. The
system is intended to dynamically externalize how a student arrives at the
final answer. Process Pad enables the documentation of students’
think-aloud narratives that would otherwise be tacit. Our focus is on
identifying and understanding key themes in creating opportunities for
students to externalize and represent their thought process using
multimodal data. From our user observations, we gleaned four design
perspectives as essential criteria based upon which we form our design
decisions: flexibility, tangibility, collaboration and affordability. Our
initial results show that for many users explaining their reasoning or
problem-solving procedure is a challenging activity in itself, and for
learners to be able to deepen their understanding by narrating or re-
enacting a process there would be many intervening steps. To address these
challenges we designed scaffolding activities, which made use of the
system’s affordances to improve students’ explanation skills.
Blikstein, P. (2012). Re-presenting complex scientific phenomena using
agent-based modeling in engineering education. In Proceedings of the ICLS (ICLS 2012), Sidney, Australia.
Blikstein, P. (2012). The making of minds: digital fabrication and the
future of stem education. Presentation at the Annual Meeting of the AERA (AERA 2012), Vancouver, Canada.
Rosenbaum, C., Blikstein, P., Roschelle, J. & Schank, P. (2012). UltraLite
Collaboration: a low-cost toolkit to promote collaborative learning in the
classroom. In Proceedings of the ICLS (ICLS 2012), Sidney, Australia.
Blikstein, P. & Worsley, M. (2012) Using automatic logging and machine
learning to uncover hidden patterns in learning to program. In Proceedings of the ICLS (ICLS 2012), Sidney, Australia.
Blikstein, P., Safdari. M. & Worsley, M. (2012). Using dynamic time warping
and cluster analysis to analyze the learning of computer programming. Paper presented at the 10th Annual International Conference of the Learning
Sciences (ICLS) and the Annual Meeting of the American Education Research Association (AERA).
Blikstein, P. (2012). Using learning analytics and educational data mining
to understand scripted and exploratory learning environments: toward a
common theoretical and methodological framework to investigate the
trajectory to expertise. Roundtable session at the Annual Meeting of the AERA (AERA 2012), Vancouver, Canada.
In this paper, we present and evaluate the design and learning affordances of Mechanix, an interactive display for children to create, record, view, and test systems of tangible simple machine components. By documenting children’s interactions, Mechanix provides opportunities for children to learn from user-generated examples and to reflect on their own designs. Through a series of user studies with children, we examine the system’s capabilities for documenting tangible design work, facilitating social learning and collaboration, and providing distinct entry points that appeal to a broad range of learners. Our results illustrate the potential of incorporating automated documentation with tangible toolkits to support learning about physics and engineering systems design.Citation:
Tiffany Tseng, Coram Bryant, and Paulo Blikstein. 2011. Collaboration through documentation: automated capturing of tangible constructions to support engineering design. In Proceedings of the 10th International Conference on Interaction Design and Children (IDC ’11). ACM, New York, NY, USA, 118-126.
Computing What the Eye Cannot See: Educational Data Mining, Learning
Analytics and Computational Techniques for Detecting and Evaluating
Learning. Paper Presented at the Annual Meeting of the American Education
Research Association (AERA).
Proceedings of the Ninth International Conference on Computer-Supported
Collaborative Learning (CSCL 2011), Hong Kong
Mechanix is a low-cost, interactive system for children to design and explore mechanical systems using computer-vision tracked, magnetic components. It employs a semi-transparent magnetic surface that supports the placement and tracking of magnetic simple machine pieces and acts as a projection screen. A back-mounted webcam captures the position of the pieces using visual tags, while a projector depicts virtual components in user-generated challenges and solutions. Designed as a museum exhibit and grounded in constructionist learning theory, Mechanix combines a virtual library of user-generated content with a tangible interface to enable asynchronous and synchronous interactions.Citation:
Tiffany Tseng, Coram Bryant, and Paulo Blikstein. 2010. Mechanix: an interactive display for exploring engineering design through a tangible interface. In Proceedings of the fifth international conference on Tangible, embedded, and embodied interaction (TEI ’11). ACM, New York, NY, USA, 265-266.
In this paper, we present an application framework for enabling education practitioners and researchers to develop interactive, multi-modal applications. These applications can be designed using typical HTML programming, and will enable a larger audience to make applications that incorporate speech recognition, gesture recognition and engagement detection. The application framework uses open-source software and inexpensive hardware that supports both multi-touch and multi-user capabilities.Citation:
Marcelo Worsley, Michael Johnston, and Paulo Blikstein. 2011. OpenGesture: a low-cost authoring framework for gesture and speech based application development and learning analytics. In Proceedings of the 10th International Conference on Interaction Design and Children (IDC ’11). ACM, New York, NY, USA, 254-256.
This paper introduces Process Pad, an interactive, low-cost multi-touch tabletop platform designed to capture students’ thought process and facilitate their explanations. The goal of Process Pad is to elicit students’ think-aloud narratives that would otherwise be tacit, in other words, “learn to explain,” and “explain to learn.” Our focus is on identifying and understanding key design factors in creating opportunities for students to externalize and represent their mental models using multimodal data. From our user observations, we gleaned four design principles as essential criteria based upon which we refined our design: flexibility, tangibility, collaboration and affordability.Citation:
Jain Kim, Colin Meltzer, Shima Salehi, and Paulo Blikstein. 2011. Process Pad: a multimedia multi-touch learning platform. In Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces (ITS ’11). ACM, New York, NY, USA, 272-273.
Microcontroller-based or physical computing devices have been used in educational settings for many years for robotics, environmental sensing, scientific experimentation, and interactive art. In this paper, we discuss design principles underlying the several available platforms for physical computing, based on a historical analysis of the development of these devices, and data from workshops conducted with students. We evaluate two of the main frameworks for physical computing (“Cricket” model and “Breakout” model), discuss affordances of each platform, and propose a new software and hardware design for microcontroller – based platforms.Citation:
Paulo Blikstein and Arnan Sipitakiat. 2011. QWERTY and the art of designing microcontrollers for children. In Proceedings of the 10th International Conference on Interaction Design and Children (IDC ’11). ACM, New York, NY, USA, 234-237.
This one-day workshop will bring together instructors who teach Interaction Design & Children at a university level from a wide spectrum of disciplines and research communities (HCI, Engineering, Design, education, Psychology and Communications). Our goal is to explore the various current ways IDC is taught, and to discuss and develop a core syllabus of literature and teaching activities for the benefit of the IDC community. Topics discussed will include: various disciplines that house IDC and their effect and needs, best practices for IDC teaching methods, and core literature (both disciplinary and multidisciplinary).Citation:
Shuli Gilutz, Tilde Bekker, Shalom Fisch, and Paulo Blikstein. 2011. Teaching interaction design & children within diverse disciplinary curricula. In Proceedings of the 10th International Conference on Interaction Design and Children (IDC ’11). ACM, New York, NY, USA, 257-259.
There is great interest in assessing student learning in unscripted, open-ended environments, but students’ work can evolve in ways that are too subtle or too complex to be detected by the human eye. In this paper, I describe an automated technique to assess, analyze and visualize students learning computer programming. I logged hundreds of snapshots of students’ code during a programming assignment, and I employ different quantitative techniques to extract students’ behaviors and categorize them in terms of programming experience. First I review the literature on educational data mining, learning analytics, computer vision applied to assessment, and emotion detection, discuss the relevance of the work, and describe one case study with a group undergraduate engineering studentsCitation:
Paulo Blikstein. 2011. Using learning analytics to assess students’ behavior in open-ended programming tasks. In Proceedings of the 1st International Conference on Learning Analytics and Knowledge (LAK ’11). ACM, New York, NY, USA, 110-116
There continues to be a call for learning approaches that promote collaboration, creativity and innovation, as well as culturally-aware, constructivist approaches to STEM learning. Unfortunately, these skills tend to lie in direct opposition to forms of the most commonly used forms of assessment – national standardized tests. Though the education research field has recognized this discontinuity, we do not currently have the technology needed to holistically assess learning which is customized, and well-adapted to the learners’ culture. Accordingly, this study endeavors to fill that gap by presenting results from a multi-modal analysis of naturally derived student data. More specifically, we used student dialogue, and student drawing – two common artifacts in project-based, constructivist learning environments – to develop predictors for student expertise in the area of engineering design. By leveraging the tools of machine learning, natural language processing, speech analysis and sentiment extraction, we were able to identify a number of distinguishing factors of learners at different levels of expertise. As such, this study motivates continued work in this space, and the development of a new paradigm for assessing student knowledge construction.Citation:
Using machine learning to examine learner’s engineering expertise using speech, text, and sketch analysis. Paper presented at the 41st Annual Meeting of the Jean Piaget Society (JPS).
Assessing student learning across a variety of environments and tasks continues to be a crucial educational concern. This task is of particular difficulty in non-traditional learning environments where students endeavor to design their own projects and engage in a hands-on educational experience. In order to improve our ability to recognize learning in these constructionist environments, this paper reports on an exploratory analysis of learning through multiple modalities: speech, sentiment and drawing. A rich set of features is automatically extracted from the data and used to identify emergent markers of expertise. Some of the most prominent markers of expertise include: user certainty, the ability to describe things efficiently and a disinclination to use unnecessary descriptors or qualifiers. Experts also displayed better organization and used less detail in their drawings. While many of these are things one would expect of an expert, there were areas in which experts looked very similar to novices. To explain this we report on learning theories that can reconcile these seemingly odd findings, and expound on how these domain-independent markers can be useful for identifying student learning over a series of activities.Citation:
Marcelo Worsley, and Paulo Blikstein. 2011. What’s an Expert? Using Learning Analytics to Identify Emergent Markers of Expertise through Automated Speech, Sentiment and Sketch Analysis. In Proceedings of the 4th International Conference on Educational Data Mining (EDM ’11). EDM, 235-240.
Blikstein, P. [symposium organizer and chair] (2010) A new age in digital
tangible interfaces for learning. In K. Gomez, L. Lyons, & J. Radinsky
(Eds.), Learning in the Disciplines: Proceedings of the 9th International
Conference of the Learning Sciences (ICLS 2010). University of Illinois at Chicago: Chicago, IL.
Using Agent-Based Computer Modeling to simulate the use of multiple
epistemological resources in the classroom. Proceedings of the annual
meeting of the Cognitive Science Society (abstracts), Portland, OR.
Can non-intelligent behavior generate intelligence? Multi-agent
computational modeling as a theory-building tool in developmental
psychology and education research. Jean Piaget Society Annual Conference
(JPS 2010), Saint Louis, MO.
Blikstein, P. (2010). Changing schools, one laser cutter at a time. FAB 6 Conference, Amsterdam, Netherlands.
Fifteen years ago, few would have predicted that children would be doing advanced robotics in middle-school. Indeed, since the seminal work by Papert, Martin, and Resnick (Martin, 1993; Resnick, et al., 1998; Resnick, Ocko, and Papert, 1991), the launch of the Lego Mindstorms platform, and the appearance of robotics competitions across the country, robotics has become a common activity in public and private schools. However, the learning revolution predicted by its proponents is still far away – such activities are oftentimes attended by males, too focused on competitions and prescribed, standardized “challenges,” and disconnected from the school curriculum. In most schools, robotics teachers conduct activities regardless of what happens in the science or math classroom.Citation:
Paulo Blikstein. 2010. Connecting the science classroom and tangible interfaces: the bifocal modeling framework. In Proceedings of the 9th International Conference of the Learning Sciences – Volume 2 (ICLS ’10), Kimberly Gomez, Leilah Lyons, and Joshua Radinsky (Eds.), Vol. 2. International Society of the Learning Sciences 128-130.
Blikstein, P. (2010). Constructionism and the next 40 years. Plenary
session, Constructionism 2010 Conference, Paris, France.
Blikstein, P. (2010). Data mining automated logs of students’ interactions
with a programming environment: a new methodological tool for the
assessment of constructionist learning. American Educational Research Association Annual Conference (AERA 2010), Denver, CO.
Worsley, M. & Blikstein, P. (2010). Learning analytics – natural
assessments for constructionist learning environments. HSTAR-Cicero Workshop on Learning, Learning Environments and Technologies.
Blikstein, P. & Wilensky, U. (2010). MaterialSim: an agent-based learning
environment for advanced scientific content. In Designs for Learning Environments of the Future (pp. 17-60), Jacobson, M. J., (Ed.), Netherlands: Springer.
Through the growing popularity of voice-enabled search, multimodal applications are finally starting to get into the hands of consumers. However, these applications are principally for mobile platforms and generally involve highly-moded interaction where the user has to click or hold a button in order to speak. Significant technical challenges remain& in bringing& multimodal interaction& to other environments such as smart living rooms and& classrooms, where users speech and gesture is directed toward large displays or interactive kiosks and the microphone and other sensors are ‘always on’. In this demonstration, we present a framework combining low cost hardware and open source software that lowers the barrier of entry for exploration of multimodal interaction in smart environments. Specifically, we will demonstrate the combination of infrared tracking, face detection, and open microphone speech recognition for media search (magicTV) and map navigation (magicMap).Citation:
Worsley, M. & Johnston, M. (2010). Multimodal interactive spaces: MagicTV
and MagicMAP. IEEE Workshop on Spoken Language Technology (SLT) Demonstration.
Sipitakiat, A. & Blikstein, P. (2010). Programmable robotics and
environmental sensing for low-income populations: design principles,
impact, and technology. In K. Gomez, L. Lyons & J. Radinsky (Eds.), Learning in the Disciplines: Proceedings of the 9th ICLS (ICLS 2010). University of Illinois at Chicago: Chicago, IL.
Programmable devices have become very popular in schools, for robotics, environmental sensing, and even interactive art. However, in developing countries, their penetration has been limited due either to unavailability or high cost. In this paper, we discuss recent work on an open-source, low-cost platform mainly designed for developing countries. We discuss its design principles, based on extensive fieldwork, as well as the learning implications, use of low-cost materials, and local construction of boards.Citation:
Arnan Sipitakiat and Paulo Blikstein. 2010. Robotics and environmental sensing for low-income populations: design principles, impact, technology, and results. In Proceedings of the 9th International Conference of the Learning Sciences – Volume 2 (ICLS ’10), Kimberly Gomez, Leilah Lyons, and Joshua Radinsky (Eds.), Vol.
2. International Society of the Learning Sciences 447-448.
[Symposium organizer and chair] Ten Constructionists Under Construction:
visions for a new age in constructionist learning. Symposium and plenary
session presented at the Constructionism 2010 Conference, Paris, France.
The Treachery of Representation: The cognitive impact of exposed
representational elements in students’ explanations of complex scientific
phenomena. Proceedings of the American Society for Engineering Education
Annual Conference (ASEE 2010), Louisville, KY.
“Programmable bricks” are microcontroller-based devices that can be used in various educational projects, such as robotic prototypes, environmental sensing, and interactive art. They have been used in educational settings for many years, but particularly in developing countries their penetration has been limited due either to unavailability or prohibitive cost. In this paper, we discuss recent work on the GoGo Board, an open-source, extensible, low-cost programmable brick mainly designed for developing countries. We discuss the board’s main design principles, which were based on our extensive fieldwork, as well as implication for learning activities, the use of low-cost materials, and local construction of boards. We use data and observations from studies in several countries such as Brazil, Mexico, and Thailand.Citation:
Arnan Sipitakiat and Paulo Blikstein. 2010. Think globally, build locally: a technological platform for low-cost, open-source, locally-assembled programmable bricks for education. In Proceedings of the fourth international conference on Tangible, embedded, and embodied interaction (TEI ’10). ACM, New York, NY, USA, 231-232.
While many of the nation’s educators and leaders are calling for students to develop 21st century competencies through student-centered, hands-on learning, most school systems continue to cling to traditional forms of instruction. This reliance on traditional forms of instruction is not without merit, however, assessment within open-ended learning environments remains difficult, and, often times, seemingly unsatisfying. This is further complicated by the large emphasis placed on students demonstrating their knowledge through standardized tests. As a way of addressing this discontinuity between practice and theory, we have worked to develop Learning Analytics—a set of multi-modal sensory inputs, that can be used to predict, understand and quantify student learning. Central to the efficacy of Learning Analytics is the belief that educators will be able to more easily adhere to learning recommendations when they are given the proper tools; in this case, tools for more accurately assessing student knowledge in open-ended learning tasks. Accordingly, this study presents finding related to one of the Learning Analytics modalities: speech. By leveraging the tools of text and speech analysis, we are able to identify domain independent markers of expertise. Some of the most prominent markers of expertise include: user certainty, the ability to describe things efficiently and a disinclination to use unnecessary descriptors or qualifiers. While many of these are things one would expect of an expert, some of them are also observed among novices. To explain this we report on learning theories that can reconcile these seemingly odd findings, and expound on how these markers can be useful for identifying student knowledge learning over the course of an intervention or classroom experience.Citation:
Worsley, M. & Blikstein P. (2010). Towards the development of learning analytics: student speech as an automatic and natural form of assessment. Paper Presented at the Annual Meeting of the American Education Research Association (AERA).
An atom is known by the company it keeps: Constructing Multi-Agent Models
in Engineering Education. International Journal of Computers for
Mathematical Learning, 14 (2), 81-119, Netherlands: Springer.
The purpose of this symposium is to move beyond speculations about how knowledge about complex systems might be important for students to understand to focus on empirical research into the learnability of these ideas. For example, do complex systems ideas represent learning challenges that are qualitatively different than learning other scientific knowledge? What are the differences in pre-conceptions students have about complex systems phenomena and more expert scientific ways of thinking in these areas? What are the profiles of successful and less successful ways of learning about complex systems conceptual perspectives? Can complex systems provide conceptual perspectives for cognitively “seeing” physical and social sciences subjects in new and interconnected ways? It is hoped the papers in this session will provide insights into these questions and other theoretical and research issues in the learning sciences.Citation:
Michael J. Jacobson, Hyo-Jeong So, June Lee, Uri Wilensky, Paolo Blikstein, Pratim Sengupta, Sharona T. Levy, and Richard Noss. 2008. Complex systems and learning: empirical research, issues, and “seeing” scientific knowledge with new eyes. In Proceedings of the 8th international conference on International conference for the learning sciences – Volume 3 (ICLS’08), Vol. 3. International Society of the Learning Sciences 266-273.
Blikstein, P. (2008). Computer modeling methodologies for investigating
classroom practices and individual cognition. Presentation at the Conference on Mixed Methods in Educational Research, Northwestern University, Evanston, IL.
Blikstein, P. (2008). Computer modeling methodologies for investigating
classroom practices and individual cognition. Presentation at the Conference on Mixed Methods in Educational Research, Northwestern University, Evanston, IL.
Sipitakiat, A. & Blikstein, P. (2008). Designing for ubiquitous robot
learning activities with the GoGo board. Paper presented at the International Conference on Embedded Systems and
Intelligent Technology (ICESIT 2008), Bangkok, Thailand.
Multi-agent simulation is a powerful technique used to encode real-world simple rules in virtual agents and then simulate their interactions . Participatory simulations are similar to multi-agent simulation except individuals play the role of virtual agents, sometimes in combination with these virtual agents . Finally, the bifocal modeling framework has enabled the examination of agents embodied in physical entities using sensors and actuators . All three of these technologies are concerned with the creation, manipulation, and development of agents in one form or another. Thus combining these three disparate systems in to one unified platform would be useful. Multi-agent simulation platforms, participatory simulations, and bifocal modeling have all been demonstrated separately in the past. However many extant systems are difficult if not impossible to integrate.Citation:
William Rand, Paulo Blikstein, and Uri Wilensky. 2008. GoGoBot: group collaboration, multi-agent modeling, and robots. In Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers (AAMAS ’08). International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, 1715-1716.
Blikstein, P., Abrahamson, D. & Wilensky, U. (2008). Groupwork as a complex
adaptive system: a methodology to model understand and design classroom
strategies for collaborative learning. Poster presented at the annual meeting of the AERA (AERA 2008-SIG ATL), Chicago, USA.
Implementing Multi-Agent Modeling in the Classroom: Lessons from Empirical
Studies in Undergraduate Engineering Education. In Jacobson, M. J.
(Organizer), Complex Systems and Learning: Empirical Research, Issues, and
“Seeing” Scientific Knowledge with New Eyes. Proceedings of the
International Conference of the Learning Sciences (ICLS), Utrecht,
This study applies agent-based modeling methodology to investigate individual and social factors underlying inequitable participation patterns observed in a real classroom in which an experimental collaborative activity was implemented. We created agent-based simulations of simplified collaborative activities and qualitatively compared results from running the model with the classroom data. We found that collaboration pedagogy emphasizing group performance may forsake individual learning, due to preference for short-term group efficacy over individual long-term learning. The study may inform professional development and pedagogical policy.Citation:
Paulo Blikstein, Dor Abrahamson, and Uri Wilensky. 2008. The classroom as a complex adaptive system: an agent-based framework to investigate students’ emergent collective behaviors. In Proceedings of the 8th international conference on International conference for the learning sciences – Volume 3 (ICLS’08), Vol. 3. International Society of the Learning Sciences 12-13.
Blikstein, P. (2008). Travels in Troy with Freire: technology as an agent
for emancipation. In P. Noguera & C. A. Torres (Eds.), Social Justice Education for Teachers: Paulo Freire and the possible dream (pp. 205-244). Rotterdam, Netherlands: Sense.
Examining group behavior and collaboration using Agent-Based Modeling and
robots. Agent 2007, Evanston, IL.
Blikstein, P. & Wilensky, U. (2007). Agent-based modeling in education:
atoms, neurons, and agents. Presentation at the Second Distributed Learning and Collaboration Symposium (DLAC II), Nanyang Technological University, Singapore.
Blikstein, P. & Wilensky, U. (2007). An empirical study of a complex
systems approach to undergraduate engineering curricula through the
construction of agent-based models. In Jacobson, M. J. (Organizer), Micki
Chi (Discussant), Complex Systems and Education: Conceptual Principles, Methodologies, and
Implications for Education. 12th Biennial Conference of the European
Association for Research on Learning and Instruction (EARLI), Budapest, Hungary.
Bifocal modeling: a framework for combining computer modeling, robotics and
real-world sensing. Paper presented at the annual meeting of the American
Educational Research Association (AERA 2007), Chicago, USA.
Blikstein, P. & Wilensky, U. (2007). Bridging the gap between neuroscience
and qualitative methods: “glass boxing” computational cognitive simulation
using agent-based modeling. Poster presented at the annual meeting of the Jean Piaget Society (JPS), Amsterdam, Netherlands.
We have been exploring the potential of agent-based modeling methodology for socialscience research and, specifically, for illuminating theoretical complementarities of cognitive and socio-constructivist conceptualizations of learning (e.g., Abrahamson & Wilensky, 2005a). The current study advances our research by applying our methodology to pedagogy research: we investigate individual and social factors underlying outcomes of implementing collaborative-inquiry classroom practice. Using bifocal modeling (Blikstein & Wilensky, 2006a), we juxtapose agent-based simulations of collaborative problem solving with real-classroom data of students’ collaboration in a demographically diverse middle-school mathematics classroom (Abrahamson & Wilensky, 2005b). We validate the computer model by comparing outcomes from running the simulation with outcomes of the real intervention. Findings are that collaboration pedagogy emphasizing group performance may forsake individual learning, because stable division-of-labor patterns emerge due to utilitarian preference of short-term production over long-term learning (Axelrod, 1997). The study may inform professional development and pedagogical policy (see interactive applet: http://ccl.northwestern.edu/research/conferences/CSCL2007/CSCL2007.html).Citation:
Dor Abrahamson, Paulo Blikstein, and Uri Wilensky. 2007. Classroom model, model classroom: computer-supported methodology for investigating collaborative-learning pedagogy. In Proceedings of the 8th international conference on Computer supported collaborative learning (CSCL’07), Clark A. Chinn, Gijsbert Erkens, and Sadhana Puntambekar (Eds.). International Society of the Learning Sciences 49-58.
We will demonstrate the integration of a software-based multi-agent modeling platform with a participatory simulation environment and a real-time control system for a physical robotic agent. Both real and virtual participants will be able to act collaboratively in a simulation that will control a physical agent. The backbone of this demonstration is a widely used, freely available, mature modeling platform (NetLogo). We posit that this technological platform can be of use for researchers interested in investigating collaborative learning and decision-making, as well as to design collaborative learning activities. We will present preliminary findings from pilot studies with the tool.Citation:
Paulo Blikstein, William Rand, and Uri Wilensky. 2007. Just a cog in the machine: participatory robotics as a tool for understanding collaborative learning and decision-making. In Proceedings of the 8th international conference on Computer supported collaborative learning (CSCL’07), Clark A. Chinn, Gijsbert Erkens, and Sadhana Puntambekar (Eds.). International Society of the Learning Sciences 84-86.
Modeling Manifold Epistemological Stances with Agent-Based Computer
Simulation. Paper presented at the annual meeting of the American
Educational Research Association (AERA 2007), Chicago, USA.
Multi-Agent Simulations as a Tool for Investigating Cognitive-Developmental
Theory. Paper presented at the annual meeting of the American Educational
Research Association (AERA 2007), Chicago, USA.
Blikstein, P. (2007). New technologies in environmental education: changing
the way we teach and learn in schools (“As novas tecnologias na educação
ambiental: instrumentos para mudar o jeito de ensinar e aprender na
escola”). In Soraia Silva de Mello (Ed.), Concepts and Practices in Environmental Education (pp. 106-112). Brasília, Brazil: Ministry of Education.
Reflections on the Feasibility of Technology as a Freirean Emancipatory
Tool in Learning Environments. Roudtable presentation at the annual meeting
of the American Educational Research Association (AERA 2007), Chicago, USA.
Blikstein, P. & Wilensky, U. (2007). Using complex systems to design and
model learning environments for advanced scientific content. Presentation at the Thirteenth International Conference on the Teaching of
Mathematical Modeling and Applications (ICTMA13), Bloomington, USA.
Blikstein, P. & Wilensky, U. (2006). A case study of multi-agent-based
simulation in undergraduate materials science education. Proceedings of the Annual Conference of the American Society for
Engineering Education (ASEE), Chicago, USA.
Blikstein, P. (2006). Assessment and its discontents (“Mal-estar na
avaliação”). In Silva, Marco (Ed.), Avaliação em Educação Online (“Assessment in Online Learning”). (pp. 123-144). Rio de Janeiro, Brazil: Ed. Loyola.
Blikstein, P. & Wilensky, U. (2006). From inert to generative modeling:
case studies of multi-agent-based simulation in undergraduate engineering
education. In D. Abrahamson (Org.), U. Wilensky (Chair), and M. Eisenberg
(Discussant), “Small steps for agents… giant steps for students? Learning
with agent-based models”. Paper presented at the annual meeting of the AERA (AERA 2006), San Francisco, USA.
Learning About Learning: Using Multi-Agent Computer Simulation to
Investigate Human Cognition. Presented at the International Conference on
Complex Systems (ICCS 2006), Boston, USA, 2006.
Blikstein, P. & Wilensky, U. (2006). MaterialSim: A constructionist
computer-based modeling environment for materials science learning. Proceedings of the Materials Science & Technology Conference of The
Minerals, Metals & Materials Society. Cincinnati, USA.
Minsky, Mind, and Models: Juxtaposing Agent-Based Computer Simulations and
Clinical-Interview Data as a Methodology for Investigating
Cognitive-Developmental Theory. Paper presented at the annual meeting of
the Jean Piaget Society (JPS 2006), Baltimore, USA.
We will demonstrate the integration of a software-based multi-agent modeling platform with a participatory simulation environment and real-time control over a physical agent (robot). Both real and virtual participants will be able to act as agents in a simulation that will control a physical agent. The backbone of this demonstration is a widely used, freely available, mature modeling platform known as NetLogo.Citation:
Paulo Blikstein, William Rand, and Uri Wilensky. 2006. Participatory, embodied, multi-agent simulation. In Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (AAMAS ’06). ACM, New York, NY, USA, 1457-1458.
Multi-agent modeling has been successfully used in several scientific fields, oftentimes transforming scientists’ practice and mindsets. Educational researchers have also realized the potential of this modeling approach for learning. Studies have suggested that students are able to understand concepts above their expected grade level after interacting with curricula developed using multi-agent simulation. However, most multi-agent models are exclusively ‘on-screen’, without connection to the physical world. Real-time model validation and realworld sensing are very challenging to accomplish with extant modeling platforms. As an attempt to address this issue, we designed a technological platform to enable students to seamlessly connect multi-agent models and electronic sensors, in real time. The platform is designed for learners to validate, refine, and debug their computer models using real-world data. This paper focuses on the technical and pedagogical aspects of this project, describing pilot studies which suggest a real-to-virtual reciprocity that catalyzes further inquiry toward deeper understanding.Citation:
Paulo Blikstein, Uri Wilensky, “The Missing Link: A Case Study of Sensing-and-Modeling Toolkits for Constructionist Scientific Investigation,” Advanced Learning Technologies, IEEE International Conference on, pp. 980-982, Sixth IEEE International Conference on Advanced Learning Technologies (ICALT’06), 2006
A Technological Platform for Trans-Media Scientific Exploration. In
Proceedings of the annual meeting of Interaction Design and Children 2006
(IDC 2006), Tampere, Finland.
Rand, W., Blikstein, P. & Wilensky, U. (2006). Widgets, planets, and
demons: the case for the integration of human, embedded, and virtual agents
via mediation. Paper presented at SwarmFest 2006, South Bend, USA.
‘Hybrid Modeling’: Advanced Scientific Investigations Linking Computer
Models and Real-World Sensing (an interactive poster). Proceedings of the
International Conference of the Learning Sciences (ICLS 2006), Bloomington,
Less is More: Agent-Based Simulation as a Powerful Learning Tool in
Materials Science. In Proceedings of the IV International Joint Conference
on Autonomous Agents and Multiagent Systems (AAMAS 2005), Utrecht, Holland.
Mixed-media learning environments. In M. Eisenberg & A. Eisenberg (Eds.), Proceedings of the Fourth International Conference for Interaction Design
and Children (IDC 2005), Boulder, Colorado.
NetLogo: Where We Are, Where We’re Going. In M. Eisenberg & A. Eisenberg
(Eds.), Proceedings of the Fourth International Conference for Interaction
Design and Children (IDC 2005), Boulder, Colorado.
GoGo Board: Augmenting Programmable Bricks for Economically Challenged
Audiences, In Proceedings of the International Conference of the Learning
Sciences (ICLS 2004), Los Angeles, USA, 2004.
In Proceedings of the International Conference on Engineering Education.
Gainesville, Florida. Paper published at the International Conference for
Engineering Education (2004).
We describe a project, The City that We Want, which enabled the constructionist use of technology within a generative theme to enable students to design and construct their ideas about how to improve life in their communities. We used a variety of computational technologies combined with crafts and scrap materials. The goal was for children to learn in a more contextualized manner important ideas in the disciplines through their projects. We designed the overall project itself as an object to think with in order to facilitate a broader reform in the schools. The willing participation, inspired projects, and commitment and development of the teachers demonstrated significant value.Citation:
Cavallo, D.; Blikstein, P.; Sipitakiat, A.; Basu, A.; Camargo, A.; de Deus Lopes, R.; Cavallo, A., “The City That We Want: generative themes, constructionist technologies and school/social change,” Advanced Learning Technologies, 2004. Proceedings. IEEE International Conference on , vol., no., pp.1034,1038, 30 Aug.-1 Sept. 2004
Blikstein, P. & Zuffo, M. K. (2004). The mermaids of electronic teaching
(“As sereias do ensino eletrônico”). In Silva, Marco (Ed.), Educação Online: teoria, prática, legislação e treinamento corporativo.
(“Online Education: theory, practice, legislation and corporate training.”). (pp. 10-37). Rio de Janeiro, Brazil: Ed. Loyola.
God hides in the details: design and implementation of technology-enabled
learning environments in public education, in Proceedings from Eurologo
2003, Porto, Portugal, 2003.
Sipitakiat, A., Blikstein, P. & Cavallo, D. (2003). GoGo board: low-cost,
programmable and reconfigurable robotics. In Sampaio, F., Motta C.,
Santoro, F. (Eds.), XIV Simpósio Brasileiro de Informática na Educação – Mini-Cursos. Rio de Janeiro, Brazil: Ed. Federal University of Rio de Janeiro.
Technology as a Trojan Horse in School Environments: The Emergence of the
Learning Atmosphere (II). In Procedings of the Interactive Computer Aided
Learning International Workshop, Carinthia Technology Institute, Villach,
Technology as a Trojan Horse in School Environments (I). In Proceedings of
the UNESCO Informatica 2002 conference, La Havana, Cuba, 2002.
The GoGo Board: Moving towards highly available computational tools in
learning environments, In Procedings of the Interactive Computer Aided
Learning International Workshop, Carinthia Technology Institute, Villach,
Comparação entre tamanhos de grãos obtidos por simulação pelo método de
Monte Carlo e resultantes de recozimento de aço Si. In Proceedings of the
54th Conference of rge Brazilian Association of Metallurgy and Materials
Science, São P., 1999, p. 1182-1191. Finalist for the “Best Paper” award in
Blikstein, P., Takanohashi, R., Landgraf, F. J. G. & Tschiptschin, A. P.
(1999). Comparison of grain sizes of silicon steels obtained experimentally
and using the Monte Carlo method (“Comparação entre tamanhos de grãos
obtidos por simulação pelo método de Monte Carlo e resultantes de
recozimento de aço Si”). In Proceedings of the 54th Conference of the Brazilian Association of
Metallurgy and Materials Science (ABM), p. 1182-1191, São Paulo, Brazil.
Blikstein, P. & Tschiptschin, A. P. (1999). Monte Carlo simulation of grain
growth (II). Materials Research, São Carlos, v. 2, n. 3, p. 133-138, July 1999.
Monte Carlo simulation of grain growth (I). In Proceedings of the IASTED Modeling and Simulation Conference, Acta Press, p. 359-363, USA, 1998.
Simulação computacional de crescimento de grão pelo método de Monte Carlo.
In Proceedings of the Encuentro de Ingeniería de Materiales, Instituto
Superior Politécnico Jose Antonio Echeverría, La Habana, Cuba, p. 314-319,
Blikstein, P. & Tschiptschin, A.P. (1997). Simulação computacional de
crescimento de grão pelo método de Monte Carlo. In Proceedings of the International Conference of Materials and Metallurgy
Technology, São Paulo, 1997.
Blikstein, P. & Worsley, M. (2011). Learning analytics: assessing
constructionist learning using machine learning. Paper presented at the Annual Meeting of the AERA (AERA 2011), New Orleans, USA.
Zain Asgar, Joshua Chan, Chang Liu, and Paulo Blikstein. 2011. LightUp: a low-cost, multi-age toolkit for learning and prototyping electronics. In Proceedings of the 10th International Conference on Interaction Design and Children (IDC ’11). ACM, New York, NY, USA, 225-226.
Daniela Steinsapir and Paulo Blikstein. 2010. Osciloscopiando: interactive video-mechanical sculpture. In Proceedings of the fifth international conference on Tangible, embedded, and embodied interaction (TEI ’11). ACM, New York, NY, USA, 411-412.